Lyu, Shiyang, Adegboye, Oyelola, Adhinugraha, Kiki, Emeto, Theophilus I., and Taniar, David (2023) Unlocking Insights: Analysing COVID-19 Lockdown Policies and Mobility Data in Victoria, Australia, through a Data-Driven Machine Learning Approach. Data, 9 (1). 3.

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Abstract

The state of Victoria, Australia, implemented one of the world’s most prolonged cumulative lockdowns in 2020 and 2021. Although lockdowns have proven effective in managing COVID-19 worldwide, this approach faced challenges in containing the rising infection in Victoria. This study evaluates the effects of short-term (less than 60 days) and long-term (more than 60 days) lockdowns on public mobility and the effectiveness of various social restriction measures within these periods. The aim is to understand the complexities of pandemic management by examining various measures over different lockdown durations, thereby contributing to more effective COVID-19 containment methods. Using restriction policy, community mobility, and COVID-19 data, a machine-learning-based simulation model was proposed, incorporating analysis of correlation, infection doubling time, and effective lockdown date. The model result highlights the significant impact of public event cancellations in preventing COVID-19 infection during short- and long-term lockdowns and the importance of international travel controls in long-term lockdowns. The effectiveness of social restriction was found to decrease significantly with the transition from short to long lockdowns, characterised by increased visits to public places and increased use of public transport, which may be associated with an increase in the effective reproduction number (Rt) and infected cases.

Item ID:	81478
Item Type:	Article (Research - C1)
ISSN:	2306-5729
Copyright Information:	© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Date Deposited:	01 Jan 2024 22:54
FoR Codes:	32 BIOMEDICAL AND CLINICAL SCIENCES > 3202 Clinical sciences > 320211 Infectious diseases @ 40% 49 MATHEMATICAL SCIENCES > 4905 Statistics > 490502 Biostatistics @ 40% 42 HEALTH SCIENCES > 4202 Epidemiology > 420205 Epidemiological modelling @ 20%
SEO Codes:	20 HEALTH > 2004 Public health (excl. specific population health) > 200406 Health protection and disaster response @ 50% 20 HEALTH > 2003 Provision of health and support services > 200303 Health surveillance @ 50%
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